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Repository Details
Build a probabilistic model from the training set of the dataset of Hacker News. It will parse the files in the training set and build a vocabulary with all the words it contains in 'Title' which is At 2018. Then for each word, compute their frequencies and the probabilities of each class (story, ask_hn, show_hn & poll). Test a Naive Bays Classifier to classify posts into data from 2019 as the testing dataset. Perform Stop-word Filtering, Word Length Filtering & Infrequent Word Filtering Experiments with the classifier.
